// Oh boy, why am I about to do this....
#ifndef NETWORK_H
#define NETWORK_H

#include "image.h"
#include "layer.h"
#include "data.h"
#include "tree.h"

typedef enum {
    CONSTANT, STEP, EXP, POLY, STEPS, SIG, RANDOM
} learning_rate_policy;

typedef struct network{
    float *workspace;
    int n;
    int batch;
    int *seen;
    float epoch;
    int subdivisions;
    float momentum;
    float decay;
    layer *layers;
    int outputs;
    float *output;
    learning_rate_policy policy;

    float learning_rate;
    float gamma;
    float scale;
    float power;
    int time_steps;
    int step;
    int max_batches;
    float *scales;
    int   *steps;
    int num_steps;
    int burn_in;

    int adam;
    float B1;
    float B2;
    float eps;

    int inputs;
    int h, w, c;
    int max_crop;
    int min_crop;
    float angle;
    float aspect;
    float exposure;
    float saturation;
    float hue;

    int gpu_index;
    tree *hierarchy;

    #ifdef GPU
    float **input_gpu;
    float **truth_gpu;
    #endif
} network;

typedef struct network_state {
    float *truth;
    float *input;
    float *delta;
    float *workspace;
    int train;
    int index;
    network net;
} network_state;

#ifdef __cplusplus
extern "C" {
#endif

#ifdef GPU
	float train_networks( network *nets, int n, data1 d, int interval );
	void sync_nets( network *nets, int n, int interval );
	float train_network_datum_gpu( network net, float *x, float *y );
	float *network_predict_gpu( network net, float *input );
	float * get_network_output_layer_gpu( network net, int i );
	float * get_network_delta_gpu_layer( network net, int i );
	float *get_network_output_gpu( network net );
	void forward_network_gpu( network net, network_state state );
	void backward_network_gpu( network net, network_state state );
	void update_network_gpu( network net );
#endif

	float get_current_rate( network net );
	int get_current_batch( network net );
	void free_network( network net );
	void compare_networks( network n1, network n2, data1 d );
	char *get_layer_string( LAYER_TYPE a );

	network make_network( int n );
	void forward_network( network net, network_state state );
	void backward_network( network net, network_state state );
	void update_network( network net );

	float train_network( network net, data1 d );
	float train_network_batch( network net, data1 d, int n );
	float train_network_sgd( network net, data1 d, int n );
	float train_network_datum( network net, float *x, float *y );

	matrix network_predict_data( network net, data1 test );
	float *network_predict( network net, float *input );
	float network_accuracy( network net, data1 d );
	float *network_accuracies( network net, data1 d, int n );
	float network_accuracy_multi( network net, data1 d, int n );
	void top_predictions( network net, int n, int *index );
	float *get_network_output( network net );
	float *get_network_output_layer( network net, int i );
	float *get_network_delta_layer( network net, int i );
	float *get_network_delta( network net );
	int get_network_output_size_layer( network net, int i );
	int get_network_output_size( network net );
	image get_network_image( network net );
	image get_network_image_layer( network net, int i );
	int get_predicted_class_network( network net );
	void print_network( network net );
	void visualize_network( network net );
	int resize_network( network *net, int w, int h );
	void set_batch_network( network *net, int b );
	int get_network_input_size( network net );
	float get_network_cost( network net );

	int get_network_nuisance( network net );
	int get_network_background( network net );

#ifdef __cplusplus
}
#endif

#endif

